KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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CDN Scalability Improvement using a Moderate Peer-assisted Method

  • Shi, Peichang (National Laboratory for Parallel and Distributed Processing, School of Computer Science, National University of Defense Technology) ;
  • Wang, Huaimin (National Laboratory for Parallel and Distributed Processing, School of Computer Science, National University of Defense Technology) ;
  • Yin, Hao (Department of Computer Science and Technology, Tsinghua University) ;
  • Ding, Bo (National Laboratory for Parallel and Distributed Processing, School of Computer Science, National University of Defense Technology) ;
  • Wang, Tianzuo (National Laboratory for Parallel and Distributed Processing, School of Computer Science, National University of Defense Technology) ;
  • Wang, Miao (Department of Computer Science and Engineering, University of Nebraska-Lincoln)
  • Received : 2011.10.19
  • Accepted : 2012.03.12
  • Published : 2012.03.30
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Abstract

Content Delivery Networks (CDN) server loads that fluctuant necessitate CDN to improve its service scalability especially when the peak load exceeds its service capacity. The peer assisted scheme is widely used in improving CDN scalability. However, CDN operators do not want to lose profit by overusing it, which may lead to the CDN resource utilization reduced. Therefore, improving CDN scalability moderately and guarantying CDN resource utilization maximized is necessary. However, when and how to use the peer-assisted scheme to achieve such improvement remains a great challenge. In this paper, we propose a new method called Dynamic Moderate Peer-assisted Method (DMPM), which uses time series analysis to predict and decide when and how many server loads needs to offload. A novel peer-assisted mechanism based on the prediction designed, which can maximize the profit of the CDN operators without influencing scalability. Extensive evaluations based on an actual CDN load traces have shown the effectiveness of DMPM.

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